AGV, AGV zero bias calibration method and storage medium

Abstract

The present invention discloses an AGV zero bias calibration method, an AGV and a storage medium thereof. The present invention controls the AGV to rotate and obtains the first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, the second sample data corresponding to the displacement parameters of the radar in the AGV and the third sample data of the angular velocity of the reference point of the AGV; determines the steering wheel calibration equation group whose first unknown is the wheel radius and the zero bias angle of the steering wheel according to the first sample data and the third sample data; determines the radar calibration equation group whose second unknown is the offset parameter of the radar according to the first solution result of the steering wheel calibration equation group, the second sample data and the third sample data; determines the zero bias calibration result of the steering wheel according to the first solution result, and determines the zero bias calibration result of the radar according to the second solution result of the radar calibration equation group, thereby improving the calibration efficiency of the AGV.

Description

Technical Field

[0001] The present invention relates to the field of AGV technology, and in particular to an AGV zero bias calibration method, an AGV and a storage medium thereof. Background Art

[0002] An automated guided vehicle (AGV) can automatically travel along a predetermined route. The steering wheel and radar of the AGV affect driving safety. Generally, zero bias calibration of the steering wheel and radar is required to ensure safe driving of the AGV.

[0003] Traditional AGVs calibrate the zero bias of the steering wheel through forward kinematics planning trajectory and inverse kinematics equations, or calibrate the zero bias of the radar by detecting the trajectory radius of the AGV turning at a preset angle. However, these methods can only calibrate the zero bias of the steering wheel or radar separately. The AGV cannot calibrate the zero bias of its steering wheel and radar together. Therefore, traditional AGVs cannot calibrate the zero bias of their steering wheel and radar together.

[0004] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of the present invention is to provide an AGV, an AGV zero bias calibration method and a storage medium thereof, aiming to realize the common zero bias calibration of the AGV steering wheel and radar and improve the calibration efficiency of the AGV.

[0006] To achieve the above object, the present invention provides an AGV zero bias calibration method, the AGV zero bias calibration method comprising the following steps:

[0007] Control the AGV to rotate and obtain first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV, and third sample data corresponding to the angular velocity of the reference point of the AGV;

[0008] Determine a steering wheel calibration equation group in which the first unknown is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data;

[0009] Determine a radar calibration equation group in which the second unknown is an offset parameter of the radar according to the first solution result of the steering wheel calibration equation group, the second sample data and the third sample data;

[0010] The zero bias calibration result of the steering wheel is determined according to the first solution result, and the zero bias calibration result of the radar is determined according to the second solution result of the radar calibration equation group.

[0011] Optionally, after the step of determining the steering wheel calibration equation group in which the first unknown is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data, the step further includes:

[0012] Converting the steering wheel calibration equations into a linear programming model;

[0013] The steering wheel calibration equation group is solved with the minimum value of the linear programming model as the target to obtain the first solution result.

[0014] Optionally, after the step of determining the steering wheel calibration equation group in which the first unknown is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data, the step further includes:

[0015] Converting the radar calibration equations into a nonlinear programming model;

[0016] The radar calibration equation group is solved with the minimum value of the nonlinear programming model as a target to obtain the second solution result.

[0017] Optionally, the step of determining a steering wheel calibration equation group in which the first unknown is the wheel radius of the steering wheel and the zero deflection angle of the steering wheel according to the first sample data and the third sample data comprises:

[0018] Acquire a first preset quantitative relationship between the rotation characteristic parameter, the angular velocity of the reference point and the first unknown number;

[0019] The value corresponding to the rotation characteristic parameter in the first preset quantitative relationship is determined according to the first sample data, and the value corresponding to the angular velocity of the reference point in the first preset quantitative relationship is determined according to the third sample data to obtain the steering wheel calibration equation group.

[0020] Optionally, the rotation characteristic parameters include the steering wheel angular velocity, rotation angle and rotation position of the steering wheel, and before the step of controlling the AGV to rotate and obtaining first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV and third sample data of the angular velocity of the reference point of the AGV, the step further includes:

[0021] determining a first quantitative relationship between the rotational position, the angular velocity of the reference point, the linear velocity component of the reference point, and the steering wheel linear velocity component of the steering wheel;

[0022] Determine a second quantitative relationship by determining a wheel radius of the steering wheel, an angular velocity of the steering wheel, the turning angle, a zero deflection angle of the steering wheel, and a linear velocity component of the steering wheel;

[0023] The first preset quantitative relationship is determined according to the first quantitative relationship and the second quantitative relationship.

[0024] Optionally, the step of determining a radar calibration equation group in which the second unknown is an offset parameter of the radar according to the first solution result of the steering wheel calibration equation group, the second sample data and the third sample data comprises:

[0025] Acquire a second preset quantitative relationship among the linear velocity component of the reference point, the displacement parameter, the angular velocity of the reference point and the second unknown number;

[0026] The radar calibration equation is obtained by determining the value corresponding to the displacement parameter in the second preset quantitative relationship according to the second sample data, determining the value corresponding to the linear velocity component of the reference point in the second preset quantitative relationship according to the first solution result and determining the value corresponding to the angular velocity of the reference point in the second preset quantitative relationship according to the third sample data.

[0027] Optionally, before the step of controlling the AGV to rotate and obtaining first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV, and third sample data of the angular velocity of the reference point of the AGV, the step further includes:

[0028] Determine a third quantitative relationship between a linear velocity component of the reference point, an angular velocity of the reference point, a displacement of the reference point, and a direction angle of the reference point;

[0029] Determining a fourth quantitative relationship between the displacement of the reference point, the displacement parameter, the direction angle of the reference point and the offset parameter;

[0030] The second preset quantitative relationship is determined according to the third quantitative relationship and the fourth quantitative relationship.

[0031] Optionally, after the step of determining the first unknown number as the linear velocity component of the reference point, the wheel radius of the steering wheel and the zero deflection angle of the steering wheel according to the first sample data and the third sample data, the step further includes:

[0032] When the first solution result of the steering wheel calibration equation group is not obtained, return to the step of controlling the rotation of the AGV and obtaining the first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, the second sample data corresponding to the displacement parameters of the radar in the AGV and the third sample data of the angular velocity of the reference point of the AGV.

[0033] In addition, to achieve the above-mentioned purpose, the present invention also provides an AGV, which includes: a memory, a processor, and an AGV zero offset calibration program stored in the memory and executable on the processor, and the AGV zero offset calibration program is configured to implement the steps of the AGV zero offset calibration method as described above.

[0034] In addition, to achieve the above-mentioned purpose, the present invention also provides a storage medium, on which an AGV zero offset calibration program is stored, and when the AGV zero offset calibration program is executed by a processor, the steps of the AGV zero offset calibration method as described above are implemented.

[0035] In an embodiment of the present invention, the AGV is controlled to rotate and obtains first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV, and third sample data of the angular velocity of the reference point of the AGV, collects measurable data in the steering wheel calibration equation group, and determines the steering wheel calibration equation group in which the first unknown number is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data. After solving the steering wheel calibration equation group, the steering wheel calibration equation group is determined according to the first solution result, the second solution result and the third solution result of the steering wheel calibration equation group. The second sample data and the third sample data determine a radar calibration equation group in which the second unknown is the offset parameter of the radar. Since the radar calibration equation group requires the solution result of the steering wheel calibration equation group, the steering wheel calibration precedes the radar calibration. The zero bias calibration result of the steering wheel is determined according to the first solution result, and the zero bias calibration result of the radar is determined according to the second solution result of the radar calibration equation group. In this way, the steering wheel calibration and the radar calibration are completed, and the steering wheel and the radar are calibrated together when the AGV rotates, and the zero bias calibration of the AGV steering wheel and the radar is realized, thereby improving the calibration efficiency of the AGV. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the structure of the AGV of the hardware operating environment involved in the embodiment of the present invention;

[0037] Figure 2 Schematic diagram of the principle of steering wheel zero bias calibration of the AGV zero bias calibration method according to an embodiment of the present invention;

[0038] Figure 3 It is a schematic diagram of the principle of displacement calculation of the reference point of the AGV zero bias calibration method according to an embodiment of the present invention;

[0039] Figure 4 It is a schematic diagram of the principle of radar zero bias calibration in the AGV zero bias calibration method according to an embodiment of the present invention;

[0040] Figure 5 It is a schematic flow chart of the first embodiment of the AGV zero bias calibration method of the present invention;

[0041] Figure 6 It is a schematic flow chart of the second embodiment of the AGV zero bias calibration method of the present invention;

[0042] Figure 7 Schematic diagram of the flow chart of the third embodiment of the AGV zero offset calibration method of the present invention.

[0043] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0044] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0045] Reference Figure 1 , Figure 1 The figure is a schematic diagram of the structure of the AGV of the hardware operating environment involved in the embodiment of the present invention.

[0046] like Figure 1 As shown, the AGV may include: a processor 1001, such as a central processing unit (CPU), a memory 1002, and a sensor 1003. The memory 1002 may be a high-speed random access memory (RAM) memory, or a stable non-volatile memory (NVM), such as a disk memory. The memory 1002 may optionally be a storage device independent of the aforementioned processor 1001. The sensor 1003 has at least one odometer and at least one radar built in.

[0047] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation of the AGV, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0048] like Figure 1 As shown, the memory 1002 as a storage medium may include an operating system, a data storage module, a network communication module, a user interface module, and an AGV zero offset calibration program.

[0049] exist Figure 1 In the AGV shown, the processor 1001 and the memory 1002 in the AGV of the embodiment of the present invention can be set in the AGV, and the AGV calls the AGV zero offset calibration program stored in the memory 1002 through the processor 1001, and executes the AGV zero offset calibration method provided by the embodiment of the present invention.

[0050] The embodiment of the present invention provides an AGV zero bias calibration method, referring to Figure 5 , Figure 5 The figure is a flow chart of a first embodiment of an AGV zero bias calibration method according to the present invention.

[0051] AGV is an unmanned vehicle. The AGV zero bias calibration principle includes the inverse kinematics model and rigid body characteristics of the omnidirectional mobile AGV.

[0052] Reference Figure 2 , XOY represents the earth coordinate system; xoy represents the vehicle coordinate system; (x i ,y i ) represents the rotation position of the i-th steering wheel relative to the reference point in the vehicle coordinate system; ω i r i Indicates the travel speed of the steering wheel; α i Indicates the target turning angle of the steering wheel; Indicates the zero deflection angle of the steering wheel; Indicates the actual turning angle of the steering wheel; It represents the component of the steering wheel's velocity in the vehicle coordinate system.

[0053] Reference Figure 3 , in the time interval [t k ,t k+1 ], the reference point is P k Position movement to P k+1 , its motion trajectory is a circular arc, Q and R represent the center and radius of the arc respectively; δ x , δ y , δ θ They respectively represent the lateral, longitudinal and angular displacements of the reference point in the vehicle coordinate system.

[0054] Reference Figure 4 , x l o l y l represents the coordinate system of the jth radar; Respectively represent the lateral, longitudinal and angular offsets of the radar installation position relative to the reference point; when the reference point is within the time interval [t k ,t k+1 ] k Position movement to P k+1 When the jth radar is arranged on the AGV, L k Position movement to L k+1 Location; They respectively represent the lateral, longitudinal and angular displacement of the jth radar in the radar coordinate system.

[0055] In this embodiment, the AGV zero bias calibration method includes:

[0056] Step S10, controlling the AGV to rotate and obtaining first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV, and third sample data corresponding to the angular velocity of the reference point of the AGV;

[0057] Controlling the AGV rotation here means controlling the AGV to spin. The preset time period refers to a period of time when the AGV rotates.

[0058] The steering wheel is used to control the movement of the AGV and change the heading of the AGV. The steering wheel here includes at least one steering wheel, which can be a single steering wheel, a double steering wheel or a triple steering wheel. The rotation characteristic parameters specifically include the steering wheel angular velocity, the rotation angle and the rotation position of the steering wheel. The first sample data refers to the value corresponding to the rotation characteristic parameter of the steering wheel collected when the AGV rotates.

[0059] The radar is used to detect the distance between the AGV and the obstacle, and the radar here includes at least one radar. The displacement parameter is specifically the relative displacement of the radar from the starting position to the end position in the preset time period. The second sample data refers to the value corresponding to the displacement parameter of the radar collected when the AGV rotates.

[0060] The reference point is the origin of the rotation position of the AGV's onboard system. The reference point can be the intersection of the diagonals of the rectangular bottom of the AGV. The reference point serves as the reference position for zero-bias calibration of the AGV's steering wheel and radar. The third sample data refers to the value corresponding to the angular velocity of the reference point collected when the AGV rotates.

[0061] In other embodiments, the rotation characteristic parameter may also include a linear velocity component of the steering wheel. The displacement parameter may also include an offset of the radar.

[0062] Specifically, when the automatic calibration of the steering wheel and radar of the AGV begins, the AGV is controlled to perform a low-speed spinning motion on a flat ground. After the AGV moves steadily, multiple sets of odometer and radar measurement data are collected and corresponding time synchronization processing is performed.

[0063] Step S20, determining a steering wheel calibration equation group in which the first unknown is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data;

[0064] The first unknown number is the wheel radius and zero deflection angle of the steering wheel to be solved in the steering wheel calibration equation group. The wheel radius of the steering wheel refers to the center radius of the wheel when the steering wheel is not deformed. The zero deflection angle of the steering wheel refers to the zero deflection angle of the steering wheel relative to the reference point.

[0065] The steering wheel calibration equation group is solved according to the first sample data and the third sample data, that is, curve fitting is performed on the steering wheel calibration equation group.

[0066] Step S30, determining a radar calibration equation group in which the second unknown is an offset parameter of the radar according to the first solution result of the steering wheel calibration equation group, the second sample data and the third sample data;

[0067] The azimuth of the reference point is determined according to the first solution result, and the radar calibration equation group in which the second unknown is the offset parameter of the radar is determined according to the azimuth of the reference point, the second sample data and the third sample data.

[0068] The linear velocity component of the reference point is the rate of change of the linear displacement of the reference point when the AGV rotates.

[0069] The first solution result is the solution value of the wheel radius and zero deflection angle of the steering wheel corresponding to the steering wheel calibration equation group. The second unknown number is the offset parameter of the radar to be solved in the radar calibration equation group. The offset parameter is the offset between the radar and the reference point in the AGV coordinate system, including the lateral, longitudinal, and angular offset of the radar relative to the reference point. In other embodiments, the offset parameter may also include only the lateral and longitudinal offsets.

[0070] The radar calibration equation group is solved according to the first solution result, the second sample data and the third sample data, that is, curve fitting is performed on the radar calibration equation group.

[0071] Step S40: determining a zero bias calibration result of the steering wheel according to the first solution result, and determining a zero bias calibration result of the radar according to the second solution result of the radar calibration equation group.

[0072] The zero bias calibration result of the steering wheel is the zero bias angle of the steering wheel. The zero bias calibration result of the radar is the zero offset parameter of the radar.

[0073] In this embodiment, the AGV is controlled to rotate and obtain first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV, and third sample data of the angular velocity of the reference point of the AGV, to collect measurable data in the steering wheel calibration equation group, and a steering wheel calibration equation group in which the first unknowns are the wheel radius and the zero deflection angle of the steering wheel is determined according to the first sample data and the third sample data. After solving the steering wheel calibration equation group, the steering wheel calibration equation group is determined according to the first solution result of the steering wheel calibration equation group, the second sample data and the third sample data. The third sample data determines a radar calibration equation group in which the second unknown is the offset parameter of the radar. Since the radar calibration equation group requires the solution of the steering wheel calibration equation group, the steering wheel calibration precedes the radar calibration. The zero bias calibration result of the steering wheel is determined according to the first solution result, and the zero bias calibration result of the radar is determined according to the second solution result of the radar calibration equation group. In this way, the steering wheel zero bias calibration and the radar zero bias calibration are completed, and the steering wheel and the radar are calibrated together when the AGV rotates, which solves the technical problem of the common zero bias calibration of the AGV steering wheel and the radar, and improves the calibration efficiency of the AGV.

[0074] Furthermore, after step S20, the method further includes:

[0075] When the first solution result of the steering wheel calibration equation group is not obtained, return to the step of controlling the rotation of the AGV and obtaining the first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, the second sample data corresponding to the displacement parameters of the radar in the AGV and the third sample data of the angular velocity of the reference point of the AGV.

[0076] Specifically, according to the collected sample data, the steering wheel calibration equation group is first solved, that is, the steering wheel calibration equation group is curve fitted. When the curve fitting is successful, that is, the first solution result is solved according to the steering wheel calibration equation group, step S30 is executed to solve the radar calibration equation group in the same way, that is, the radar calibration equation group is curve fitted. When the curve fitting is unsuccessful, that is, the first solution result cannot be solved according to the steering wheel calibration equation group, the step S10 is returned to execute until the solution is successful.

[0077] In this embodiment, when the solution of the steering wheel calibration equation group cannot be obtained according to the collected sample data, the sample data is re-collected for solution until the solution of the steering wheel calibration equation group can be obtained, so that the AGV zero bias calibration method can continue to be executed when the currently collected sample data cannot successfully solve the steering wheel calibration equation group, filter out inaccurate or unreasonable sample data, improve the accuracy and availability of the collected sample data, and improve the recyclability of the AGV steering wheel and radar zero bias calibration, thereby improving the feasibility of AGV calibration.

[0078] Based on the above embodiment, the second embodiment of the present invention provides an AGV zero bias calibration method, referring to Figure 6 , Figure 6 The figure is a flow chart of a second embodiment of an AGV zero offset calibration method according to the present invention.

[0079] In this embodiment, the rotation characteristic parameters include the steering wheel angular velocity, rotation angle and rotation position of the steering wheel, and before step S10, the following steps are further included:

[0080] Step S01, determining a first quantitative relationship between the rotation position, the angular velocity of the reference point, the linear velocity component of the reference point and the steering wheel linear velocity component of the steering wheel;

[0081] The rotation position is the coordinate of the steering wheel relative to the reference point. The angular velocity of the reference point is positive in the counterclockwise direction. Figure 2 , the linear velocity component of the reference point is the linear velocity component in the earth coordinate system XOY, and the linear velocity component of the steering wheel is the linear velocity component in the vehicle coordinate system xoy.

[0082] The first quantitative relationship is:

[0083]

[0084] Among them, the rotation position and the angular velocity of the reference point are defined as (x i ,y i ) and ω, define the linear velocity component of the reference point as v X 、v Y , define the steering wheel linear velocity component as i represents the i-th (i=1,…,n) steering wheel.

[0085] It should be noted that the first quantitative relationship indicates that the linear velocity component of each steering wheel in the vehicle body coordinate system is determined according to the linear velocity component of the reference point.

[0086] Step S02, determining a second quantitative relationship by determining a wheel radius of the steering wheel, an angular velocity of the steering wheel, the turning angle, a zero deflection angle of the steering wheel, and a linear velocity component of the steering wheel;

[0087] The steering wheel angular velocity is the steering angular velocity of the steering wheel. The turning angle is the turning angle formed by the steering wheel turning within a preset time period.

[0088] The second quantitative relationship is:

[0089]

[0090] Among them, the steering wheel linear velocity component is defined as The wheel radius, angular velocity, turning angle and zero deviation angle of the steering wheel are defined as r i ,ω i, α i and i represents the i-th (i=1,…,n) steering wheel.

[0091] It should be noted that the second quantitative relationship indicates that the linear velocity component of each steering wheel in the vehicle body coordinate system can be derived according to the geometric relationship between the linear velocity component of the steering wheel and the rotation characteristic parameter of the steering wheel.

[0092] Step S03: determining the first preset quantity relationship according to the first quantity relationship and the second quantity relationship.

[0093] Under the condition that the ground is flat and the AGV wheels do not slip, according to the first and second quantitative relationships, we can get:

[0094]

[0095] Among them, the wheel radius and zero deflection angle are unknown variables. The linear velocity components of the reference point cannot be measured by sensors and are unknown parameters. The angular velocity, turning angle, angular velocity of the reference point and the rotation position of the steering wheel can all be measured by sensors and are known parameters.

[0096] In order to facilitate the solution of the variable r i , Will As the variable to be solved, and use the addition and subtraction elimination method to eliminate the unknown parameters v X 、v Y , thus obtaining 2(n-1) independent equations, that is, the first preset quantitative relationship is:

[0097] Ax=B

[0098] in,

[0099]

[0100]

[0101]

[0102]

[0103]

[0104] Δ x1i =x1-x i ,Δ y1i =y1-y i

[0105] In this embodiment, a first quantitative relationship is established based on the relationship between the linear velocity component of the reference point and the linear velocity component of the steering wheel, a second quantitative relationship is established based on the geometric relationship between the linear velocity component of the steering wheel and the rotation characteristic parameter of the steering wheel, and then a first preset quantitative relationship is determined based on the first quantitative relationship and the second quantitative relationship. Since the first preset quantitative relationship is used to establish a steering wheel calibration equation group, constructing the first preset quantitative relationship ensures the feasibility of the steering wheel zero bias calibration and improves the success rate of the AGV steering wheel zero bias calibration.

[0106] Further, step S20 includes:

[0107] Step S04, obtaining a first preset quantitative relationship between the rotation characteristic parameter, the angular velocity of the reference point and the first unknown number;

[0108] In this embodiment, an omnidirectional mobile AGV with n (n>1) steering wheels is defined, and the first preset quantity relationship is:

[0109] Ax=B

[0110] in,

[0111]

[0112]

[0113]

[0114]

[0115]

[0116] Δ x1i =x1-x i ,Δ y1i =y1-y i

[0117] The wheel radius, angular velocity, turning angle and zero deviation angle of the i-th steering wheel are defined as r i ,ω i , α i and (x i ,y i ) is the coordinate of the i-th steering wheel relative to the reference point C, where i represents the i-th (i=1,…,n) steering wheel.

[0118] Step S05, determining a value corresponding to the rotation characteristic parameter in the first preset quantitative relationship according to the first sample data and determining a value corresponding to the angular velocity of the reference point in the first preset quantitative relationship according to the third sample data, to obtain the steering wheel calibration equation group.

[0119] Specifically, the first sample data corresponding to the rotation characteristic parameters of the steering wheel measured by the sensor and the third sample data corresponding to the angular velocity of the reference point are substituted into the first preset quantitative relationship, that is, the first preset quantitative relationship is calibrated, and generally multiple groups of sample data are used for calibration.

[0120] In this embodiment, the steering wheel calibration equation group is established by substituting the collected sample data into the first preset quantitative relationship to implement the steering wheel zero bias calibration, so as to obtain the steering wheel zero bias calibration result, ensure the accuracy of the steering wheel zero bias calibration, and further improve the accuracy of the steering wheel zero bias calibration through multiple groups of sample data, thereby improving the calibration efficiency of the AGV.

[0121] Furthermore, after step S20, the method further includes:

[0122] Step S06, converting the steering wheel calibration equation group into a linear programming model;

[0123] The coefficient matrices A and B in the steering wheel calibration equation group are usually calculated from the collected sample data. Multiple groups of sample data are used to calibrate the steering wheel calibration equation group, and the calibrated steering wheel calibration equation group is converted into a linear programming model.

[0124] Step S07, solving the steering wheel calibration equation group with the minimum value of the linear programming model as the target to obtain the first solution result.

[0125] In this embodiment, the minimum value of the linear programming model is:

[0126] min‖Ax-B‖ 2

[0127] in,

[0128]

[0129]

[0130]

[0131]

[0132]

[0133] Δ x1i =x1-x i ,Δ y1i =y1-y i

[0134] Define an omnidirectional mobile AGV with n (n>1) steering wheels, and define the wheel radius, angular velocity, turning angle and zero deviation angle of the i-th steering wheel as r i ,ωi , α i and (x i ,y i ) is the rotation position of the i-th steering wheel relative to the reference point C, where i represents the i-th (i=1,…,n) steering wheel.

[0135] In other embodiments, instead of taking the minimum value of the linear programming model to solve the steering wheel calibration equation group, the steering wheel calibration equation group can be solved by taking a fixed value of the linear programming model.

[0136] Since multiple groups of sample data are generally used to calibrate the steering wheel calibration equation group, the solution of the steering wheel calibration equation group is converted into a solution with the minimum value of the linear programming model as the target.

[0137] Specifically, a curve fitting method is used to calculate the minimum linear programming model, that is, to calculate the first solution, specifically the solution x of the steering wheel calibration equation group.

[0138] In this embodiment, the steering wheel calibration equation group is converted into a minimum value solution through a linear programming model, so that the solution of the steering wheel calibration equation group can be realized, that is, the feasibility of the steering wheel zero bias calibration is improved, thereby improving the feasibility of the AGV zero bias calibration, thereby improving the calibration efficiency of the AGV.

[0139] Based on the above embodiments, the third embodiment of the present invention provides an AGV zero bias calibration method, referring to Figure 7 , Figure 7 The figure is a flow chart of a third embodiment of an AGV zero offset calibration method according to the present invention.

[0140] In this embodiment, before step S10, the method further includes:

[0141] Step S001, determining a third quantitative relationship between a linear velocity component of the reference point, an angular velocity of the reference point, a displacement of the reference point and a direction angle of the reference point;

[0142] The angular velocity of the reference point is positive in the counterclockwise direction. Figure 2 , the linear velocity component of the reference point is the linear velocity component under the earth's rotation position system XOY. The displacement of the reference point is the relative displacement of the reference point from the starting position to the end position within the preset time period. The direction angle of the reference point is the angle change when the reference point rotates within the preset time.

[0143] The third quantitative relationship is:

[0144]

[0145] Among them, by t k Time to t k+1At this moment, the reference point is from point P k Position movement to point P k+1 Position, the direction angle change of the reference point is δ θ =ω(t k+1 -t k )=ωΔ t The radius of the circle is The center of the circle is Q. In the time interval [t k ,t k+1 ], the reference point is from point P k Position movement to point P k+1 The horizontal, vertical and angular offsets of the reference point are defined as δ x , δ y , δ θ .

[0146] It should be noted that the third quantitative relationship indicates that the displacement of the reference point can be determined according to the geometric relationship of the reference point.

[0147] Step S002, determining a fourth quantitative relationship between the displacement of the reference point, the displacement parameter, the direction angle of the reference point and the offset parameter;

[0148] The displacement parameter is the relative displacement of the radar from the starting position to the end position within the preset time period. The displacement parameter includes the lateral, longitudinal and angular displacement. The offset parameter is the offset between the radar and the reference point in the vehicle coordinate system. The offset parameter includes the lateral, longitudinal and angular offset.

[0149] The fourth quantitative relationship is:

[0150]

[0151] Among them, the jth radar is defined from point L k Position movement to point L k+1 The relative displacements of the radar’s displacement parameters in the horizontal, vertical, and angular directions are defined as In the vehicle coordinate system xoy, there is an offset between the radar and the reference point. The lateral, longitudinal and angular offsets of the offset parameters are defined as j (j=1,2,…,m) represents the jth radar.

[0152] It should be noted that the fourth quantitative relationship expression can derive the displacement parameter of the radar according to the displacement of the reference point.

[0153] Step S003: Determine the second preset quantity relationship according to the third quantity relationship and the fourth quantity relationship.

[0154] In this embodiment, an omnidirectional mobile AGV with m (m>1) radars is defined, and the second preset quantity relationship is:

[0155] Cy=D

[0156] in,

[0157] y=[y1,y2,…,y m ] T ,

[0158]

[0159] D j =[sinδ θ 1-cosδ θ ] T

[0160] Define the direction angle of the reference point as δ θ The radar displacement includes the radar's lateral displacement, longitudinal displacement and angular displacement, which are defined as and Radar offset includes the radar's lateral offset, longitudinal offset and angular offset, which are defined as and Where j (j=1,2,…,m) represents the jth radar.

[0161] In this embodiment, a third quantitative relationship is established based on the geometric relationship of the reference point, a fourth quantitative relationship is established based on the relationship between the displacement of the reference point and the displacement parameter of the radar, and then the second preset quantitative relationship is determined based on the third quantitative relationship and the fourth quantitative relationship. Since the second preset quantitative relationship is used to establish a radar calibration equation group, constructing the second preset quantitative relationship ensures the feasibility of radar zero bias calibration and improves the success rate of AGV radar zero bias calibration.

[0162] Step S30 includes:

[0163] Step S004, obtaining a second preset quantitative relationship between the linear velocity component of the reference point, the displacement parameter, the angular velocity of the reference point and the second unknown number;

[0164] In this embodiment, an omnidirectional mobile AGV with m (m>1) radars is defined, and the second preset quantitative relationship is obtained according to the linear velocity component of the reference point, the displacement parameter, the angular velocity and the second unknown number:

[0165] Cy=D

[0166] in,

[0167] y=[y1,y2,…,y m ] T ,

[0168]

[0169] D j =[sinδ θ 1-cosδ θ ] T

[0170] Define the direction angle of the reference point as δ θ The radar displacement includes the radar's lateral displacement, longitudinal displacement and angular displacement, which are defined as and Radar offset includes the radar's lateral offset, longitudinal offset and angular offset, which are defined as for, and Where j (j=1,2,…,m) represents the jth radar.

[0171] Step S005, determining the value corresponding to the displacement parameter in the second preset quantitative relationship according to the second sample data, determining the value corresponding to the linear velocity component of the reference point in the second preset quantitative relationship according to the first solution result and determining the value corresponding to the angular velocity in the second preset quantitative relationship according to the third sample data, and obtaining the radar calibration equation.

[0172] Specifically, the second sample data corresponding to the displacement parameter of the radar measured by the sensor and the third sample data corresponding to the angular velocity of the reference point are substituted into the second preset quantitative relationship, that is, the second preset quantitative relationship is calibrated, and generally multiple groups of sample data are used for calibration.

[0173] In this embodiment, the radar calibration equation group is established by substituting the collected sample data into the second preset quantitative relationship to implement the radar zero bias calibration, so as to obtain the radar zero bias calibration result, ensure the accuracy of the radar zero bias calibration, and further improve the accuracy of the radar zero bias calibration through multiple groups of sample data, thereby improving the calibration efficiency of the AGV.

[0174] Furthermore, after step S20, the method further includes:

[0175] Step S006, converting the radar calibration equation group into a nonlinear programming model;

[0176] The coefficient matrices C and D in the radar calibration equation group are usually calculated from the collected sample data. Multiple groups of sample data are used to calibrate the radar calibration equation group, and the calibrated radar calibration equation group is converted into a nonlinear programming model.

[0177] Step S007, solving the radar calibration equation group with the minimum value of the nonlinear programming model as the target to obtain the second solution result.

[0178] In this embodiment, the minimum value of the nonlinear programming model is:

[0179] min||Cy-D|| 2

[0180] in,

[0181] y=[y1,y2,…,y m ] T ,

[0182]

[0183] D j =[sinδ θ 1-cosδ θ ] T

[0184] Define an omnidirectional mobile AGV with m (m>1) radars, and define the direction angle of the reference point as δ θ The radar displacement includes the radar's lateral displacement, longitudinal displacement and angular displacement, which are defined as and Radar offset includes the radar's lateral offset, longitudinal offset and angular offset, which are defined as and Where j (j=1,2,…,m) represents the jth radar.

[0185] In other embodiments, the radar calibration equation group may be solved by taking a fixed value of the linear programming model instead of taking the minimum value of the linear programming model.

[0186] Since multiple groups of sample data are generally used to calibrate the radar calibration equation group, the solution of the radar calibration equation group is converted into a solution with the minimum value of the nonlinear programming model as the target.

[0187] Specifically, a curve fitting method is used to calculate the minimum value of the nonlinear programming model, that is, to calculate the second solution, specifically the solution y of the radar calibration equation group.

[0188] In this embodiment, the radar calibration equation group is converted into a minimum value solution through a nonlinear programming model, so that the solution of the radar calibration equation group can be realized, that is, the feasibility of radar zero bias calibration is improved, thereby improving the feasibility of AGV zero bias calibration and improving the calibration efficiency of AGV.

[0189] In addition, an embodiment of the present invention also provides an AGV, which includes: a memory, a processor, and an AGV zero offset calibration program stored in the memory and executable on the processor, wherein the AGV zero offset calibration program is configured to implement the steps of any embodiment of the above AGV zero offset calibration method.

[0190] In addition, an embodiment of the present invention further provides a storage medium, on which an AGV zero offset calibration program is stored. When the AGV zero offset calibration program is executed by a processor, the relevant steps of any embodiment of the above AGV zero offset calibration method are implemented.

[0191] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0192] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0193] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0194] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An AGV zero bias calibration method, characterized in that: The AGV zero bias calibration method comprises the following steps: Control the AGV to rotate and obtain first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV, and third sample data corresponding to the angular velocity of the reference point of the AGV; Determine a steering wheel calibration equation group in which the first unknown is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data; Determine a radar calibration equation group in which the second unknown is an offset parameter of the radar according to a first solution result of the steering wheel calibration equation group, the second sample data and the third sample data; The zero bias calibration result of the steering wheel is determined according to the first solution result, and the zero bias calibration result of the radar is determined according to the second solution result of the radar calibration equation group.

2. The AGV zero bias calibration method according to claim 1, characterized in that: After the step of determining the steering wheel calibration equation group in which the first unknown is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data, the method further includes: Converting the steering wheel calibration equations into a linear programming model; The steering wheel calibration equation group is solved with the minimum value of the linear programming model as the target to obtain the first solution result.

3. The AGV zero bias calibration method according to claim 1, characterized in that: After the step of determining the radar calibration equation group in which the second unknown is the offset parameter of the radar according to the first solution result of the steering wheel calibration equation group, the second sample data and the third sample data, the method further includes: Converting the radar calibration equations into a nonlinear programming model; The radar calibration equation group is solved with the minimum value of the nonlinear programming model as a target to obtain the second solution result.

4. The AGV zero bias calibration method according to claim 1, characterized in that: The step of determining the steering wheel calibration equation group in which the first unknown is the wheel radius of the steering wheel and the zero deflection angle of the steering wheel according to the first sample data and the third sample data comprises: Acquire a first preset quantitative relationship between the rotation characteristic parameter, the angular velocity of the reference point and the first unknown number; The value corresponding to the rotation characteristic parameter in the first preset quantitative relationship is determined according to the first sample data, and the value corresponding to the angular velocity of the reference point in the first preset quantitative relationship is determined according to the third sample data to obtain the steering wheel calibration equation group.

5. The AGV zero bias calibration method according to claim 4, characterized in that: The rotation characteristic parameters include the steering wheel angular velocity, rotation angle and rotation position of the steering wheel. Before the step of controlling the AGV to rotate and obtaining the first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, the second sample data corresponding to the displacement parameters of the radar in the AGV and the third sample data corresponding to the angular velocity of the reference point of the AGV, the step further includes: determining a first quantitative relationship between the rotational position, the angular velocity of the reference point, the linear velocity component of the reference point, and the steering wheel linear velocity component of the steering wheel; Determining a second quantitative relationship among a wheel radius of the steering wheel, an angular velocity of the steering wheel, the turning angle, a zero deflection angle of the steering wheel, and a linear velocity component of the steering wheel; The first preset quantitative relationship is determined according to the first quantitative relationship and the second quantitative relationship.

6. The AGV zero bias calibration method according to claim 1, characterized in that: The step of determining the radar calibration equation group in which the second unknown is the offset parameter of the radar according to the first solution result of the steering wheel calibration equation group, the second sample data and the third sample data comprises: Acquire a second preset quantitative relationship among the linear velocity component of the reference point, the displacement parameter, the angular velocity of the reference point and the second unknown number; The radar calibration equation is obtained by determining the value corresponding to the displacement parameter in the second preset quantitative relationship according to the second sample data, determining the value corresponding to the linear velocity component of the reference point in the second preset quantitative relationship according to the first solution result and determining the value corresponding to the angular velocity of the reference point in the second preset quantitative relationship according to the third sample data.

7. The AGV zero bias calibration method according to claim 6, characterized in that: Before the step of controlling the AGV to rotate and obtaining first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, second sample data corresponding to the displacement parameters of the radar in the AGV, and third sample data corresponding to the angular velocity of the reference point of the AGV, the method further includes: Determine a third quantitative relationship between a linear velocity component of the reference point, an angular velocity of the reference point, a displacement of the reference point, and a direction angle of the reference point; Determining a fourth quantitative relationship between the displacement of the reference point, the displacement parameter, the direction angle of the reference point and the offset parameter; The second preset quantitative relationship is determined according to the third quantitative relationship and the fourth quantitative relationship.

8. The AGV zero bias calibration method according to any one of claims 1 to 7, characterized in that: After the step of determining the steering wheel calibration equation group in which the first unknown is the wheel radius and the zero deflection angle of the steering wheel according to the first sample data and the third sample data, the method further includes: When the first solution result of the steering wheel calibration equation group is not obtained, return to the step of controlling the rotation of the AGV and obtaining the first sample data corresponding to the rotation characteristic parameters of the steering wheel in the AGV within a preset time period, the second sample data corresponding to the displacement parameters of the radar in the AGV and the third sample data corresponding to the angular velocity of the reference point of the AGV.

9. An AGV, characterized in that: The AGV includes: A memory, a processor, and an AGV zero offset calibration program stored in the memory and executable on the processor, wherein the AGV zero offset calibration program is configured to implement the steps of the AGV zero offset calibration method according to any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium stores an AGV zero offset calibration program, and when the AGV zero offset calibration program is executed by the processor, the steps of the AGV zero offset calibration method according to any one of claims 1 to 8 are implemented.

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